class_docstr: Generate views by applying a sequence of transformations (augmentations) on 
  given batched graphs. Class objects callable via method :meth:`views_fn`.
  
  Args:
      fn_sequence (list): A list of callable view generation functions (classes).
docstr: Method to be called when :class:`Sequential` object is called.
  
  Args:
      data (:class:`torch_geometric.data.Data`): The input graph or batched graphs.
      
  :rtype: :class:`torch_geometric.data.Data`.  
docstr_tok: ["Method","to","be","called","when",":","class",":","`","Sequential","`","object","is","called",".","Args",":","data","(",":","class",":","`","torch_geometric.data.Data","`",")",":","The","input","graph","or","batched","graphs",".",":","rtype",":",":","class",":","`","torch_geometric.data.Data","`","."]
code: def views_fn(self, data):
      r"""Method to be called when :class:`Sequential` object is called.
  
      Args:
          data (:class:`torch_geometric.data.Data`): The input graph or batched graphs.
  
      :rtype: :class:`torch_geometric.data.Data`.
      """
      for fn in self.fn_sequence:
          data = fn(data)
  
      return data
  
file_path: DIG/dig/sslgraph/method/contrastive/views_fn/combination.py
imports: import random
  from torch_geometric.data import Batch
label_desc: Use image node_id 3 for calling the Sequential obj's underlying member method code with example usage: obj.views_fn(data) and returns: data